Evolutionary Conservation and Functional Constraint of TP53 Mutation Hotspots Across Mammalian Species

Evolutionary Conservation and Functional Constraint of TP53 Mutation Hotspots Across Mammalian Species | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Evolutionary Conservation and Functional Constraint of TP53 Mutation Hotspots Across Mammalian Species Ritika Rajendra Rawat¹, Sermarani Nadar², Gursimran Kaur Uppal³ This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9299199/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The tumour suppressor protein TP53 is essential for preserving genomic integrity and is among the most frequently mutated genes in human cancers. Mutations in TP53 show a non-uniform distribution and are concentrated at specific residues, commonly referred to as mutation hotspots. Although these positions are well characterised in clinical studies, their evolutionary behaviour across species remains insufficiently understood. In this study, TP53 protein sequences from ten mammalian species were analysed to investigate conservation patterns at six canonical hotspot residues (R175, G245, R248, R249, R273, and R282). Multiple sequence alignment was performed, followed by residue-level conservation scoring and statistical comparison with non-hotspot positions. Hotspot residues exhibited significantly higher conservation (mean ≈ 0.95) compared to non-hotspot residues (mean ≈ 0.78), with the difference confirmed by the Mann–Whitney U test (p = 0.034). In addition, hotspot positions showed reduced variability, indicating stronger evolutionary constraint. Sequence identity analysis revealed moderate to high similarity (69–92%) across species, supporting the robustness of the dataset. Structural and alignment-based observations further demonstrated that hotspot residues are localised within a highly conserved functional domain. These findings suggest that TP53 mutation hotspots represent evolutionarily constrained residues embedded within critical structural regions, providing insight into their susceptibility to recurrent mutation in cancer. Biological sciences/Cancer Biological sciences/Computational biology and bioinformatics Biological sciences/Evolution Biological sciences/Genetics Figures Figure 1 Figure 2 Figure 3 1. INTRODUCTION The TP53 gene encodes a transcription factor that functions as a central regulator of cellular responses to genomic stress, including DNA repair, apoptosis, and cell cycle arrest [1,2]. Due to its critical role in maintaining genomic stability, TP53 is among the most frequently mutated genes in human cancers [3,4]. Notably, mutations in TP53 are show a non-uniform distribution and are concentrated at specific residues, commonly referred to as mutation hotspots [5,6]. These hotspots are predominantly located within the DNA-binding domain, a region essential for transcriptional regulation and protein functionality. These observations indicate that mutation hotspots are likely driven by functional vulnerability within structurally constrained regions [7]. However, it remains unclear whether TP53 hotspot residues are uniquely conserved compared to other residues within functionally constrained regions. Comparative sequence analysis across species provides an effective framework for identifying conserved and variable regions within proteins. By analysing evolutionary patterns, it is possible to infer functional importance and structural constraints. In this study, TP53 sequences from ten mammalian species were analysed using multiple sequence alignment and statistical methods to evaluate conservation patterns at hotspot residues. The objective was to determine whether these positions exhibit distinct evolutionary characteristics compared to non-hotspot residues. 2. MATERIALS AND METHODS 2.1 Sequence Retrieval TP53 protein sequences were obtained from publicly available databases, including UniProt and NCBI Protein [1]. Only complete and high-confidence sequences were included, while partial or low-quality entries were excluded to ensure dataset reliability. 2.2 Multiple Sequence Alignment Multiple sequence alignment was performed using Clustal Omega with default parameters [2,3]. The alignment ensured consistent positional comparison across homologous residues. 2.3 Conservation Analysis Residue-level conservation scores were calculated based on the frequency of the most common amino acid at each alignment position. 2.4. Hotspot Residue Selection Six canonical TP53 hotspot residues (R175, G245, R248, R249, R273, and R282) were selected based on established cancer mutation studies [4-6]. 2.5. Statistical Analysis Differences in conservation between hotspot and non-hotspot residues were evaluated using the Mann–Whitney U test. 2.6. Sequence Identity Analysis Pairwise sequence identity was assessed to evaluate evolutionary divergence among species[7]. 2.7. Phylogenetic Analysis Phylogenetic relationships were inferred using standard evolutionary approaches [8,9]. 2.8 Computational Tools All analyses were performed using Python libraries including Biopython, NumPy, SciPy, and Matplotlib. 3. RESULTS 3.1. Conservation of TP53 Hotspot Residues Conservation analysis revealed that TP53 hotspot residues are highly conserved across mammalian species, with scores ranging from approximately 0.91 to 1.00 and a mean value of 0.95. In contrast, non-hotspot residues exhibited greater variability, with a mean conservation score of approximately 0.78. 3.2. Statistical Comparison Statistical analysis demonstrated a significant difference between hotspot and non-hotspot conservation scores (p = 0.034), indicating stronger evolutionary constraint at hotspot positions. 3.3. Sequence Identity Analysis Pairwise sequence identity ranged from approximately 69% to 92%, reflecting moderate to high similarity across species and confirming the evolutionary diversity of the dataset. 3.4. Multiple Sequence Alignment Patterns The alignment revealed strong conservation within the central DNA-binding domain, while terminal regions displayed increased variability. 3.5. Phylogenetic Relationships Phylogenetic analysis demonstrated clustering of TP53 sequences according to species relationships, consistent with evolutionary divergence patterns. 4. DISCUSSION The present study demonstrates that TP53 mutation hotspots are significantly more conserved than non-hotspot residues across mammalian species. This finding suggests that these positions are subject to strong evolutionary constraint, likely reflecting their essential functional roles. The localisation of hotspot residues within the DNA-binding domain supports their structural and functional importance [1,2]. Mutations at these positions are known to disrupt protein activity and contribute to cancer development [3]. Evolutionary conservation is typically associated with functional importance, as critical residues are preserved through selective pressure [4]. The observed conservation patterns in this study are consistent with this principle and indicate that hotspot residues are integral to TP53 function. Furthermore, sequence identity analysis confirms that the dataset captures meaningful evolutionary variation, strengthening the validity of the results. Despite divergence across species, key functional regions remain conserved. These findings suggest that mutation hotspots in TP53 arise from structural and functional sensitivity rather than random distribution, providing an evolutionary explanation for their recurrent occurrence in cancer. 5. LIMITATIONS This study is based on computational analysis and does not include experimental validation. Future studies incorporating structural and experimental approaches would provide further insights. 6. CONCLUSION TP53 mutation hotspots represent evolutionarily constrained residues located within a highly conserved functional domain. Their strong conservation and reduced variability highlight their importance in maintaining protein function and explain their frequent mutation in cancer. Declarations 7. AUTHOR CONTRIBUTIONS Ms Ritika Rajendra. Rawat conceptualised the study, performed sequence analysis, conducted statistical analysis, generated figures, and wrote the manuscript. Mrs Sermarani Nadar contributed to data interpretation and methodology refinement. Dr Gursimran Kaur Uppal contributed to the manuscript review and supervision. 8. FUNDING No external funding was received. 9. CONFLICT OF INTEREST The authors declare no conflict of interest. 10. DATA AVAILABILITY All data used in this study are publicly available from established biological databases. The reference human TP53 protein sequence was obtained from UniProt (accession ID: P04637 ) and NCBI Protein database. Additional TP53 protein sequences from mammalian species were retrieved from NCBI Protein and Ensembl Genome Browser using gene-specific queries. The accession identifiers for representative sequences used in this study include: NP_001120705.1 (Mus musculus), P10361 (Rattus norvegicus), P56424 (Macaca mulatta), XP_016786959.2 (Pan troglodytes), Q29537 (Canis lupus familiaris), P41685 (Felis catus), P67939 (Bos taurus), Q9TUB2 (Sus scrofa), XP_003416950.3 (Loxodonta africana), and XP_036692565.1 (Balaenoptera musculus). The processed multiple sequence alignment (TP53_MSA.fasta, conservation analysis results (TP53_hotspot_analysis.csv), and computational workflow are provided as supplementary materials. No additional datasets were generated or used beyond publicly accessible resources. References Levine, A. J. (1997). p53, the cellular gatekeeper for growth and division. Cell, 88 (3), 323–331. https://doi.org/10.1016/S0092-8674(00)81871-1 Vousden, K. H., & Lane, D. P. (2007). p53 in health and disease. Nature Reviews Molecular Cell Biology, 8 (4), 275–283. https://doi.org/10.1038/nrm2147 Olivier, M., Hollstein, M., & Hainaut, P. (2010). TP53 mutations in human cancers. Cold Spring Harbor Perspectives in Biology, 2 (1), a001008. https://doi.org/10.1101/cshperspect.a001008 Vogelstein, B., Lane, D., & Levine, A. J. (2000). Surfing the p53 network. Nature, 408 (6810), 307–310. https://doi.org/10.1038/35042675 Kandoth, C., McLellan, M. D., Vandin, F., et al. (2013). Mutational landscape and significance across major cancer types. Nature, 502 (7471), 333–339. https://doi.org/10.1038/nature12634 Joerger, A. C., & Fersht, A. R. (2008). Structural biology of the tumor suppressor p53. Annual Review of Biochemistry, 77 , 557–582. https://doi.org/10.1146/annurev.biochem.77.060806.091238 Koonin, E. V. (2010). The origin and early evolution of eukaryotes in light of phylogenomics. Genome Biology, 11 (5), 209. https://doi.org/10.1186/gb-2010-11-5-209 Sievers, F., & Higgins, D. G. (2018). Clustal Omega for making accurate alignments. Methods in Molecular Biology, 1731 , 33–48. https://doi.org/10.1007/978-1-4939-7644-2_4 Eddy, S. R. (2004). What is a hidden Markov model? Nature Biotechnology, 22 (10), 1315–1316. https://doi.org/10.1038/nbt1004-1315 Ashkenazy, H., Abadi, S., Martz, E., et al. (2016). ConSurf: evolutionary conservation analysis of macromolecules. Nucleic Acids Research, 44 (W1), W344–W350. https://doi.org/10.1093/nar/gkw408 UniProt Consortium. (2021). UniProt: the universal protein knowledgebase. Nucleic Acids Research, 49 (D1), D480–D489. https://doi.org/10.1093/nar/gkaa1100 Sayers, E. W., Cavanaugh, M., Clark, K., et al. (2022). GenBank. Nucleic Acids Research, 50 (D1), D161–D164. https://doi.org/10.1093/nar/gkab1135 Nei, M., & Kumar, S. (2000). Molecular evolution and phylogenetics . Oxford University Press. Yang, Z. (2006). Computational molecular evolution . Oxford University Press. Dayhoff, M. O., Schwartz, R. M., & Orcutt, B. C. (1978). A model of evolutionary change in proteins. Atlas of Protein Sequence and Structure, 5 (3), 345–352. Henikoff, S., & Henikoff, J. G. (1992). Amino acid substitution matrices from protein blocks. Proceedings of the National Academy of Sciences, 89 (22), 10915–10919. https://doi.org/10.1073/pnas.89.22.10915 Robinson, A. B., & Robinson, L. R. (1991). Distribution of glutamine and asparagine residues. Proceedings of the National Academy of Sciences, 88 (20), 8880–8884. Felsenstein, J. (1985). Confidence limits on phylogenies. Evolution, 39 (4), 783–791. https://doi.org/10.1111/j.1558-5646.1985.tb00420.x Tamura, K., Stecher, G., Kumar, S. (2021). MEGA11: Molecular evolutionary genetics analysis version 11. Molecular Biology and Evolution, 38 (7), 3022–3027. https://doi.org/10.1093/molbev/msab120 Hainaut, P., & Pfeifer, G. P. (2016). Somatic TP53 mutations in the era of genome sequencing. Cold Spring Harbor Perspectives in Medicine, 6 (11), a026179. https://doi.org/10.1101/cshperspect.a026179 Additional Declarations No competing interests reported. Supplementary Files SupplementaryTableS1IdentityMatrix.txt TP53EvolutionaryFunctionalAnalysis.ipynb Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9299199","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":616376170,"identity":"dfc3ec98-425c-4f27-83d0-a70fe8f2fbf5","order_by":0,"name":"Ritika Rajendra 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1","display":"","copyAsset":false,"role":"figure","size":69286,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConservation comparison of hotspot and non-hotspot residues\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9299199/v1/41e244514fd4a8224f9ddc0b.png"},{"id":106066642,"identity":"0f1fae18-23aa-4f15-a9dc-fc981ca43216","added_by":"auto","created_at":"2026-04-03 05:38:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":120168,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMultiple sequence alignment of TP53\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9299199/v1/43e5d3bb84cd853ba2d56365.png"},{"id":106066643,"identity":"64668bcb-83c7-4bb3-af7f-28c262897f59","added_by":"auto","created_at":"2026-04-03 05:38:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":41044,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic Tree of TP53\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9299199/v1/f462091565e3cc4940160ad1.png"},{"id":108804844,"identity":"de8b23f9-5a47-4543-a512-ada78ba9e8c9","added_by":"auto","created_at":"2026-05-08 15:23:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":315427,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9299199/v1/266f977f-2743-4ef5-8ab7-346fb4f99e1c.pdf"},{"id":106066640,"identity":"29739615-b9a0-40c6-9284-55f6e7895b15","added_by":"auto","created_at":"2026-04-03 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INTRODUCTION","content":"\u003cp\u003eThe TP53 gene encodes a transcription factor that functions as a central regulator of cellular responses to genomic stress, including DNA repair, apoptosis, and cell cycle arrest [1,2]. Due to its critical role in maintaining genomic stability, TP53 is among the most frequently mutated genes in human cancers [3,4].\u003c/p\u003e\n\u003cp\u003eNotably, mutations in TP53 are show a non-uniform distribution and are concentrated at specific residues, commonly referred to as mutation hotspots [5,6]. These hotspots are predominantly located within the DNA-binding domain, a region essential for transcriptional regulation and protein functionality.\u003c/p\u003e\n\u003cp\u003eThese observations indicate that mutation hotspots are likely driven by functional vulnerability within structurally constrained regions [7]. However, it remains unclear whether TP53 hotspot residues are uniquely conserved compared to other residues within functionally constrained regions.\u003c/p\u003e\n\u003cp\u003eComparative sequence analysis across species provides an effective framework for identifying conserved and variable regions within proteins. By analysing evolutionary patterns, it is possible to infer functional importance and structural constraints.\u003c/p\u003e\n\u003cp\u003eIn this study, TP53 sequences from ten mammalian species were analysed using multiple sequence alignment and statistical methods to evaluate conservation patterns at hotspot residues. The objective was to determine whether these positions exhibit distinct evolutionary characteristics compared to non-hotspot residues.\u003c/p\u003e"},{"header":" 2. MATERIALS AND METHODS","content":"\u003ch2\u003e2.1\u0026nbsp;Sequence Retrieval\u003c/h2\u003e\n\u003cp\u003eTP53 protein sequences were obtained from publicly available databases, including UniProt and NCBI Protein [1]. Only complete and high-confidence sequences were included, while partial or low-quality entries were excluded to ensure dataset reliability.\u003c/p\u003e\n\u003ch2\u003e2.2\u0026nbsp;Multiple Sequence Alignment\u003c/h2\u003e\n\u003cp\u003eMultiple sequence alignment was performed using Clustal Omega with default parameters [2,3]. The alignment ensured consistent positional comparison across homologous residues.\u003c/p\u003e\n\u003ch2\u003e2.3\u0026nbsp;Conservation Analysis\u003c/h2\u003e\n\u003cp\u003eResidue-level conservation scores were calculated based on the frequency of the most common amino acid at each alignment position.\u003c/p\u003e\n\u003ch2\u003e2.4. Hotspot Residue Selection\u003c/h2\u003e\n\u003cp\u003eSix canonical TP53 hotspot residues (R175, G245, R248, R249, R273, and R282) were selected based on established cancer mutation studies [4-6].\u003c/p\u003e\n\u003ch2\u003e2.5.\u0026nbsp;Statistical Analysis\u003c/h2\u003e\n\u003cp\u003eDifferences in conservation between hotspot and non-hotspot residues were evaluated using the Mann\u0026ndash;Whitney U test.\u003c/p\u003e\n\u003ch2\u003e2.6. Sequence Identity Analysis\u003c/h2\u003e\n\u003cp\u003ePairwise sequence identity was assessed to evaluate evolutionary divergence among species[7].\u003c/p\u003e\n\u003ch2\u003e2.7.\u0026nbsp;Phylogenetic Analysis\u003c/h2\u003e\n\u003cp\u003ePhylogenetic relationships were inferred using standard evolutionary approaches [8,9].\u003c/p\u003e\n\u003ch2\u003e2.8 Computational Tools\u003c/h2\u003e\n\u003cp\u003eAll analyses were performed using Python libraries including Biopython, NumPy, SciPy, and Matplotlib.\u003c/p\u003e"},{"header":"3. RESULTS","content":"\u003ch2\u003e3.1.\u0026nbsp;Conservation\u0026nbsp;of\u0026nbsp;TP53\u0026nbsp;Hotspot\u0026nbsp;Residues\u003c/h2\u003e\n\u003cp\u003eConservation analysis revealed that TP53 hotspot residues are highly conserved across mammalian species, with scores ranging from approximately 0.91 to 1.00 and a mean value of 0.95. In contrast, non-hotspot residues exhibited greater variability, with a mean conservation score of approximately 0.78.\u003c/p\u003e\n\u003ch2\u003e3.2.\u0026nbsp;Statistical Comparison\u003c/h2\u003e\n\u003cp\u003eStatistical analysis demonstrated a significant difference between hotspot and non-hotspot conservation scores (p = 0.034), indicating stronger evolutionary constraint at hotspot positions.\u003c/p\u003e\n\u003ch2\u003e3.3. \u0026nbsp;Sequence Identity Analysis\u003c/h2\u003e\n\u003cp\u003ePairwise sequence identity ranged from approximately 69% to 92%, reflecting moderate to high similarity across species and confirming the evolutionary diversity of the dataset.\u003c/p\u003e\n\u003ch2\u003e3.4.\u0026nbsp;Multiple Sequence Alignment Patterns\u003c/h2\u003e\n\u003cp\u003eThe alignment revealed strong conservation within the central DNA-binding domain, while terminal regions displayed increased variability.\u003c/p\u003e\n\u003ch2\u003e3.5.\u0026nbsp;Phylogenetic Relationships\u003c/h2\u003e\n\u003cp\u003ePhylogenetic analysis demonstrated clustering of TP53 sequences according to species relationships, consistent with evolutionary divergence patterns.\u003c/p\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThe present study demonstrates that TP53 mutation hotspots are significantly more conserved than non-hotspot residues across mammalian species. This finding suggests that these positions are subject to strong evolutionary constraint, likely reflecting their essential functional roles.\u003c/p\u003e\n\u003cp\u003eThe localisation of hotspot residues within the DNA-binding domain supports their structural and functional importance \u0026nbsp;[1,2]. Mutations at these positions are known to disrupt protein activity and contribute to cancer development [3].\u003c/p\u003e\n\u003cp\u003eEvolutionary conservation is typically associated with functional importance, as critical residues are preserved through selective pressure [4]. The observed conservation patterns in this study are consistent with this principle and indicate that hotspot residues are integral to TP53 function.\u003c/p\u003e\n\u003cp\u003eFurthermore, sequence identity analysis confirms that the dataset captures meaningful evolutionary variation, strengthening the validity of the results. Despite divergence across species, key functional regions remain conserved.\u003c/p\u003e\n\u003cp\u003eThese findings suggest that mutation hotspots in TP53 arise from structural and functional sensitivity rather than random distribution, providing an evolutionary explanation for their recurrent occurrence in cancer.\u003c/p\u003e"},{"header":"5.\tLIMITATIONS","content":"\u003cp\u003eThis study is based on computational analysis and does not include experimental validation. Future studies incorporating structural and experimental approaches would provide further insights.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"6.\tCONCLUSION","content":"\u003cp\u003eTP53 mutation hotspots represent evolutionarily constrained residues located within a highly conserved functional domain. Their strong conservation and reduced variability highlight their importance in maintaining protein function and explain their frequent mutation in cancer.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e7.\u0026nbsp;AUTHOR\u0026nbsp;CONTRIBUTIONS\u003c/h2\u003e\n\u003cp\u003eMs\u0026nbsp;Ritika\u0026nbsp;Rajendra.\u0026nbsp;Rawat\u0026nbsp;conceptualised\u0026nbsp;the\u0026nbsp;study,\u0026nbsp;performed\u0026nbsp;sequence\u0026nbsp;analysis,\u0026nbsp;conducted statistical analysis, generated figures, and wrote the manuscript. Mrs Sermarani Nadar contributed to data interpretation and methodology refinement. Dr Gursimran Kaur Uppal contributed to the manuscript review and supervision.\u003c/p\u003e\n\u003ch2\u003e8.\u0026nbsp;FUNDING\u003c/h2\u003e\n\u003cp\u003eNo\u0026nbsp;external funding\u0026nbsp;was\u0026nbsp;received.\u003c/p\u003e\n\u003ch2\u003e9.\u0026nbsp;CONFLICT\u0026nbsp;OF\u0026nbsp;INTEREST\u003c/h2\u003e\n\u003cp\u003eThe\u0026nbsp;authors\u0026nbsp;declare\u0026nbsp;no\u0026nbsp;conflict\u0026nbsp;of\u0026nbsp;interest.\u003c/p\u003e\n\u003ch2\u003e10.\u0026nbsp;DATA\u0026nbsp;AVAILABILITY\u003c/h2\u003e\n\u003cp\u003eAll data used in this study are publicly available from established biological databases. The reference human TP53 protein sequence was obtained from UniProt (accession ID: \u003cstrong\u003eP04637\u003c/strong\u003e) and NCBI Protein database. Additional TP53 protein sequences from mammalian species were retrieved from NCBI Protein and Ensembl Genome Browser using gene-specific queries.\u003c/p\u003e\n\u003cp\u003eThe accession identifiers for representative sequences used in this study include: \u003cstrong\u003eNP_001120705.1\u003c/strong\u003e (Mus musculus), \u003cstrong\u003eP10361\u003c/strong\u003e (Rattus norvegicus), \u003cstrong\u003eP56424\u003c/strong\u003e (Macaca mulatta), \u003cstrong\u003eXP_016786959.2\u003c/strong\u003e (Pan troglodytes), \u003cstrong\u003eQ29537\u003c/strong\u003e (Canis lupus familiaris), \u003cstrong\u003eP41685\u003c/strong\u003e (Felis catus), \u003cstrong\u003eP67939\u003c/strong\u003e (Bos taurus), \u003cstrong\u003eQ9TUB2\u003c/strong\u003e (Sus scrofa), \u003cstrong\u003eXP_003416950.3\u003c/strong\u003e (Loxodonta africana), and \u003cstrong\u003eXP_036692565.1\u003c/strong\u003e (Balaenoptera musculus).\u003c/p\u003e\n\u003cp\u003eThe processed multiple sequence alignment (TP53_MSA.fasta, conservation analysis results (TP53_hotspot_analysis.csv), and computational workflow are provided as supplementary materials. No additional datasets were generated or used beyond publicly accessible resources.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLevine, A. J. (1997). p53, the cellular gatekeeper for growth and division. \u003cem\u003eCell, 88\u003c/em\u003e(3), 323\u0026ndash;331. https://doi.org/10.1016/S0092-8674(00)81871-1\u003c/li\u003e\n\u003cli\u003eVousden, K. H., \u0026amp; Lane, D. P. (2007). p53 in health and disease. \u003cem\u003eNature Reviews Molecular Cell Biology, 8\u003c/em\u003e(4), 275\u0026ndash;283. https://doi.org/10.1038/nrm2147\u003c/li\u003e\n\u003cli\u003eOlivier, M., Hollstein, M., \u0026amp; Hainaut, P. (2010). TP53 mutations in human cancers. \u003cem\u003eCold Spring Harbor Perspectives in Biology, 2\u003c/em\u003e(1), a001008. https://doi.org/10.1101/cshperspect.a001008\u003c/li\u003e\n\u003cli\u003eVogelstein, B., Lane, D., \u0026amp; Levine, A. J. (2000). 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B., \u0026amp; Robinson, L. R. (1991). Distribution of glutamine and asparagine residues. \u003cem\u003eProceedings of the National Academy of Sciences, 88\u003c/em\u003e(20), 8880\u0026ndash;8884.\u003c/li\u003e\n\u003cli\u003eFelsenstein, J. (1985). Confidence limits on phylogenies. \u003cem\u003eEvolution, 39\u003c/em\u003e(4), 783\u0026ndash;791. https://doi.org/10.1111/j.1558-5646.1985.tb00420.x\u003c/li\u003e\n\u003cli\u003eTamura, K., Stecher, G., Kumar, S. (2021). MEGA11: Molecular evolutionary genetics analysis version 11. \u003cem\u003eMolecular Biology and Evolution, 38\u003c/em\u003e(7), 3022\u0026ndash;3027. https://doi.org/10.1093/molbev/msab120\u003c/li\u003e\n\u003cli\u003eHainaut, P., \u0026amp; Pfeifer, G. P. (2016). Somatic TP53 mutations in the era of genome sequencing. \u003cem\u003eCold Spring Harbor Perspectives in Medicine, 6\u003c/em\u003e(11), a026179. https://doi.org/10.1101/cshperspect.a026179\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9299199/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9299199/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The tumour suppressor protein TP53 is essential for preserving genomic integrity and is among the most frequently mutated genes in human cancers. Mutations in TP53 show a non-uniform distribution and are concentrated at specific residues, commonly referred to as mutation hotspots. Although these positions are well characterised in clinical studies, their evolutionary behaviour across species remains insufficiently understood.\nIn this study, TP53 protein sequences from ten mammalian species were analysed to investigate conservation patterns at six canonical hotspot residues (R175, G245, R248, R249, R273, and R282). Multiple sequence alignment was performed, followed by residue-level conservation scoring and statistical comparison with non-hotspot positions.\nHotspot residues exhibited significantly higher conservation (mean ≈ 0.95) compared to non-hotspot residues (mean ≈ 0.78), with the difference confirmed by the Mann–Whitney U test (p = 0.034). In addition, hotspot positions showed reduced variability, indicating stronger evolutionary constraint. Sequence identity analysis revealed moderate to high similarity (69–92%) across species, supporting the robustness of the dataset. Structural and alignment-based observations further demonstrated that hotspot residues are localised within a highly conserved functional domain.\nThese findings suggest that TP53 mutation hotspots represent evolutionarily constrained residues embedded within critical structural regions, providing insight into their susceptibility to recurrent mutation in cancer.","manuscriptTitle":"Evolutionary Conservation and Functional Constraint of TP53 Mutation Hotspots Across Mammalian Species","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-03 05:38:07","doi":"10.21203/rs.3.rs-9299199/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2497af7f-d716-43e8-8f29-931147f77c85","owner":[],"postedDate":"April 3rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":65589975,"name":"Biological sciences/Cancer"},{"id":65589976,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":65589977,"name":"Biological sciences/Evolution"},{"id":65589978,"name":"Biological sciences/Genetics"}],"tags":[],"updatedAt":"2026-05-06T12:26:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-03 05:38:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9299199","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9299199","identity":"rs-9299199","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}